Pages that link to "Item:Q1747739"
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The following pages link to Testing independence in high dimensions with sums of rank correlations (Q1747739):
Displaying 31 items.
- Generalizing Distance Covariance to Measure and Test Multivariate Mutual Dependence (Q151604) (← links)
- Central limit theorem for linear spectral statistics of large dimensional Kendall's rank correlation matrices and its applications (Q820817) (← links)
- Rank-based tests of cross-sectional dependence in panel data models (Q830595) (← links)
- Testing independence in high dimensions using Kendall's tau (Q1662048) (← links)
- Asymptotic power of Rao's score test for independence in high dimensions (Q1715529) (← links)
- An extreme-value approach for testing the equality of large U-statistic based correlation matrices (Q1740532) (← links)
- Testing independence in high dimensions with sums of rank correlations (Q1747739) (← links)
- High-dimensional consistent independence testing with maxima of rank correlations (Q1996766) (← links)
- Distance-based and RKHS-based dependence metrics in high dimension (Q1996774) (← links)
- Limiting spectral distribution of large dimensional Spearman's rank correlation matrices (Q2146458) (← links)
- Testing for independence of high-dimensional variables: \(\rho V\)-coefficient based approach (Q2181735) (← links)
- Multivariate tests of independence and their application in correlation analysis between financial markets (Q2196137) (← links)
- Maximum pairwise Bayes factors for covariance structure testing (Q2233577) (← links)
- Randomized incomplete \(U\)-statistics in high dimensions (Q2284368) (← links)
- A necessary test for complete independence in high dimensions using rank-correlations (Q2350669) (← links)
- Asymptotically independent U-statistics in high-dimensional testing (Q2656592) (← links)
- Testing conditional multivariate rank correlations: the effect of institutional quality on factors influencing competitiveness (Q2677124) (← links)
- Marginal Distance and Hilbert-Schmidt Covariances-Based Independence Tests for Multivariate Functional Data (Q5076363) (← links)
- High-dimensional proportionality test of two covariance matrices and its application to gene expression data (Q5880120) (← links)
- Distribution-Free Consistent Independence Tests via Center-Outward Ranks and Signs (Q5881094) (← links)
- On eigenvalues of a high-dimensional Kendall's rank correlation matrix with dependence (Q6084694) (← links)
- Max-sum test based on Spearman's footrule for high-dimensional independence tests (Q6170540) (← links)
- Rank-based indices for testing independence between two high-dimensional vectors (Q6192324) (← links)
- Testing for independence in high dimensions based on empirical copulas (Q6192330) (← links)
- Rank-based max-sum tests for mutual independence of high-dimensional random vectors (Q6193027) (← links)
- Testing for practically significant dependencies in high dimensions via bootstrapping maxima of \(U\)-statistics (Q6550967) (← links)
- Statistical Inferences for Complex Dependence of Multimodal Imaging Data (Q6567943) (← links)
- Distance correlation test for high-dimensional independence (Q6589588) (← links)
- Limit theorems for non-degenerate U-statistics of block maxima for time series (Q6595783) (← links)
- Independence test via mutual information in the presence of measurement errors (Q6643228) (← links)
- An adaptive test based on Kendall's tau for independence in high dimensions (Q6669473) (← links)
